Adaptive digital beamforming architecture and algorithm for nulling mainlobe and multiple sidelobe radar jammers while preserving monopulse ratio angle estimation accuracy

ABSTRACT

Monopulse radar operation is improved by nulling a single mainlobe jammer and multiple sidelobe jammers while maintaining the angle measurement accuracy of the monopulse ratio. A sidelobe jammer cancelling adaptive array is cascaded with a mainlobe jammer canceller, imposing a mainlobe maintenance technique or constrained adaptation during the sidelobe jammer cancellation process so that results of the sidelobe jammer cancellation process do not distort the subsequent mainlobe jammer cancellation process. The sidelobe jammers and the mainlobe jammer are thus cancelled sequentially in separate processes.

RELATED APPLICATIONS

This application is related to Yu and Murrow application Ser. No.07/807,548 filed concurrently herewith and assigned to the instantassignee.

BACKGROUND OF THE INVENTION

This invention generally relates to radar techniques for determiningangular location of a target and, more particularly, to an improvementin the monopulse technique so as to maintain accuracy of the monopulseratio in the presence of jamming by adaptively and optimally suppressingthe jamming before forming the conventional sum Σ and difference Δ beamoutput signals for monopulse processing.

The monopulse technique is a radar technique in which the angularlocation of a target can be determined within fractions of a beamwidthby comparing measurements received from two or more simultaneous beams.This technique for direction of arrival (DOA) estimation of a target iswidely employed in modern surveillance and tracking radar. See, forexample, D. K. Barton, "Modern Radar Systems Analysis," Artech House(1988), M. Sherman, "Monopulse Principles and Techniques," Artech House(1988), and I. Leanov and K. I. Fomichev, "Monopulse Radar," ArtechHouse (1986). In a typical phased array or digital beamforming (DBF)radar, one beam is formed in transmission and two beams are formed onreception for angle measurement.

The monopulse technique may be implemented for a linear array of Nantenna elements which provide respective signals x (0), . . . , x (N-1)to the beamforming network from the elemental receiver. The outputsignals of the beamforming network are the sum Σ and difference Δsignals which are processed in a processor to generate an output signalθ representing the direction of arrival estimation.

In the beamforming network, each of N input signals is split into twopaths, linearly weighted, and then added together. The sum Σ anddifference Δ signals may be expressed in the form

    Σ=W.sub.Σ.sup.H x                              (1)

    Δ=W.sub.Δ.sup.H x                              (2)

respectively, where W.sub.Σ is real and even weighting, W.sub.Δ ispurely imaginary and odd weighting, H indicates complex conjugatetranspose and x is the vector of the measurements. When there is nojamming, Taylor and Bayliss weightings are typically used for sum beamsand difference beams, respectively, so as to have a narrow mainlobe andlow sidelobes. In the presence of jamming, the weights are adapted so asto form nulls responsive to the jammers. The quiescent Taylor andBayliss weightings are designed for reducing the sidelobes in apractical system. See Y. T. Lo and S. W. Lee, "Antenna Handbook, Theory,Applications, and Design", Van Nostrand Reinhold Company, New York(1988), Chapter 13.

In a typical antenna pattern, the mainlobe of the pattern is a centralbeam surrounded by minor lobes, commonly referred to as sidelobes.Typically, it is desired to have a narrow mainlobe, high gain and lowsidelobes so that the desired target within the mainlobe is enhanced andthe response to clutter and jamming outside the mainlobe is attenuated.The sidelobe levels of an antenna pattern can be described in any ofseveral ways. The most common expression is the relative sidelobe level,defined as the peak level of the highest sidelobe relative to the peaklevel of the main beam. Sidelobe levels can also be quantified in termsof their absolute level relative to isotropic.

The term "monopulse" refers to the fact that the echo from a singletransmitted pulse returning from a target is used to measure the angleof the target, and that, typically, one beam (instead of two beams) isformed in transmission, and two beam output signals are formed onreception for angle measurement. The sum beam pattern has a symmetricalamplitude profile with its maximum at the boresight, and the differencebeam pattern has an antisymmetrical amplitude profile with zero responseat the boresight. The DOA of a target signal can be determinedaccurately through a look-up table by evaluating the monopulse ratio,i.e., the real part of Δ/Σ. In fact, for a noiseless case and foruniform weighting, the monopulse ratio is exactly given by ##EQU1##where T =sin (θ) and θ is the desired DOA, d is the array elementspacing, N is the number of sensor elements, and λ is the wavelength.This equation enables T and the corresponding θ to be determinedexactly. In the presence of noise, the development of the DOA maximumlikelihood estimator also leads naturally to monopulse processing usingsum and difference beams. See R. C. Davis, L. E. Brennan, and I. S.Reed, "Angle Estimation with Adaptive Arrays in External Noise Field,"IEEE Trans on Aerospace and Electronic Systems, Vol. AES-12, No. 2,March 1976. For zero-mean noise, the estimator is unbiased with meansquare error (MSE) given by ##EQU2## SNR is the signal-to-noise ratio atthe elemental level, and g (T) is the two-way sum beam antenna pattern.

Various authors have defined the monopulse sensitivity factor indifferent ways (see R. R. Kinsey, "Monopulse Difference Slope and GainStandards," IRE Trans., Vol AP-10, pp. 343-344, May 1962). In thisapplication, the monopulse sensitivity factor is defined as the constantof proportionality required in the denominator of theroot-mean-square-error (RMSE) to convert the square root of twice theboresight signal-to-noise ratio in the beam to RMSE. Defined in thismanner, the monopulse sensitivity factor has the desirable property ofcontaining all target angle-of-arrival information. "f" is the monopulsefunction and "f dot" is the derivative of the monopulse function. See D.J. Murrow, "Height Finding and 3D Radar", Chapter 20, Radar Handbook(2nd Edition), McGraw-Hill.

This technique can also be considered for a planar array where thetarget azimuth and elevation angles are desired. In this setup, a set ofsum (Σ_(e)) and difference (Δ_(e)) beam output signals are formed alongthe elevation axis with input signals from each column of sensors. TheΣ_(e) beam output signals are then linearly combined in an adder to formthe sum (Σ=Σ_(a) Σ_(e)) and difference (Δ_(A) =Δ_(a) Σ_(e)) beam outputsignals along the azimuth axis, where Σ_(a) and Δ_(a) are the effectiverow sum beam and row difference beam, respectively. Similarly, the Δ_(e)beams are linearly combined in an adder to form the sum (Δ_(E) =Σ_(a)Δ_(e)) and difference (Δ.sub.Δ =Δ_(a) Δ_(e)) beam output signals alongthe azimuth axis. Monopulse ratios along azimuth or elevation directioncan then be formed giving the azimuth and elevation DOA estimates byusing the following equations: ##EQU3## These derivations make use ofthe separable property of the planar array patterns.

The monopulse technique for DOA estimation fails when there is sidelobejamming (SLJ) and/or main lobe jamming (MLJ). If not effectivelycountered, electronic jamming prevents successful radar target detectionand tracking. The situation is exacerbated by introduction of stealthtechnology to reduce the radar cross section (RCS) of unfriendlyaircraft targets. The frequency dependence of the RCS encourages use oflower microwave frequency bands for detection. This leads to largeapertures to achieve angular resolution. Large apertures to achievesmall beamwidth results in interception of more jamming. On the otherhand, constrained apertures lead to wider beamwidth, which impliesinterception of more mainlobe jamming.

Heretofore, no viable or practical technique for cancelling simultaneousmainlobe and sidelobe jammers has been developed or fielded in a radar.This makes the conception and development of such technique one of themore pressing and critical issues facing radar today. The challenge isto develop adaptive beamforming architectures and signal processingalgorithms to cancel mainlobe and sidelobe jammers while maintainingtarget detection and angle estimation accuracy on mainlobe targets.

Clark (see C. R. Clark, "Main Beam Jammer Cancellation and Target AngleEstimation with a Polarization-Agile Monopulse Antenna," 1989 IEEE RadarConference, Mar. 29-30, 1989, Dallas, Tex., pp. 95-100) addresses theproblem of simultaneous mainlobe and sidelobe jamming cancellation buthis work is distinguished from the present invention in three respects.First, Clark does not include the requirement of maintaining themonopulse ratio. Second, his approach uses the main array and sidelobeauxiliary array simultaneously. Third, as a consequence of using thearrays simultaneously, Clark's approach does not include mainlobemaintenance, thereby introducing distortion into the main beam.

It is therefore an object of the invention to adaptively and optimallysuppress the jamming of monopulse radar before the sum and differencebeam output signals are formed for monopulse processing.

Another object of the invention is to cancel a single mainlobe jammerand multiple sidelobe jammers of monopulse radar while maintainingtarget detection and angle estimation accuracy on mainlobe targets.

Another object of the invention is to incorporate a sidelobe jammingcanceller and a mainlobe jamming canceller in a monopulse radar digitalbeamforming (DBF) architecture so as to maintain the monopulse accuracyfor DOA estimation for mainlobe targets.

According to the basic principles of the invention, jammers of monopulseradar are nulled before forming the final Σ and Δ beam output signalsfor monopulse processing. This is accomplished by a filtering approachtogether with a mainlobe maintenance technique. Identical processing isalso required for both the Σ and Δ beams in order to form an identicalset of nulls responsive to the sidelobe jammers.

In a specific implementation of the invention, the sidelobe jammers(SLJs) are first suppressed but not the mainlobe jammer (MLJ). It isessential to include an appropriate mainlobe maintenance (MLM) techniqueat a prefiltering stage to prevent adverse interaction between the twotechniques. The MLM technique prevents the sidelobe cancelling adaptivearray technique from interfering with the mainlobe canceller (MLC). Theresulting beams are adapted using Applebaum's orthogonal nullingtechnique to cancel the mainlobe jammer along each axis while formingthe monopulse ratio in the other axis. (See S. P. Applebaum and R.Wasiewicz, Main Beam Jammer Cancellation for Monopulse Sensors, FinalTech. Report DTIC RADC-TR-86-267, December, 1984.)

In accordance with a preferred embodiment of the invention, a monopulseradar system is provided having an adaptive array antenna, a mainlobecanceller, and a monopulse processor for determining angle of arrival,the adaptive array antenna comprising multiple elemental sensors, themonopulse processor estimating angle of arrival using sum and differencebeam output signals, and the mainlobe canceller generating the sum anddifference beam output signals which, for one class of rectangular arraywith independent horizontal and vertical beamforming, can be expressedas a product of elevation and azimuth factors for use by the monopulseprocessor, simultaneously yielding an undistorted elevation angularmeasurement by cancelling a mainlobe jammer with nulls in azimuth and anundistorted azimuth angular measurement by cancelling the mainlobejammer with nulls in elevation. Preprocessing means are coupled to theadaptive array antenna for forming an identical set of nulls responsiveto jammers before the sum and difference beam output signals are formedfor monopulse processing. The preprocessing comprises means for applyingadaptive weights to the measured signal for suppression of sidelobejamming. Means are provided for generating adaptive weight using asample matrix inverse estimate with appropriate mainlobe maintenance.Additional means are provided for maintaining the mainlobe duringpreprocessing and still further means are provided for coupling theadaptive array in cascade with the mainlobe canceller.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, aspects and advantages will be betterunderstood from the following detailed description of a preferredembodiment of the invention with reference to the drawings, in which:

FIG. 1 is a block diagram showing a monopulse beamforming network forestimating direction of arrival;

FIG. 2 is a detailed block diagram of a beamforming network;

FIG. 3 is a perspective view of a monopulse radar sum beam antennapattern;

FIG. 4 is a graph of sum and difference beam patterns for monopulseantennas;

FIG. 5 is a graph of the monopulse ratio;

FIG. 6 is a block diagram of a monopulse radar;

FIG. 7 is a block diagram showing a sum-difference mainlobe canceller;

FIG. 8 is a block diagram showing a mainlobe canceller for monopulseprocessing;

FIG. 9 is a block diagram showing an adaptive array for forming sum anddifference beam output signals; and

FIG. 10 is a simplified block diagram of the architecture of theinvention, combining adaptive array and mainlobe canceller for monopulseprocessing.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT OF THE INVENTION

In FIG. 1, a monopulse technique for DOA estimation is shown implementedfor a linear array of antenna elements 10₀ to 10_(N-1) which providerespective signals x (0), . . . , x (N-1) to the beam forming (BF)network 12 for combining the input signals from the elemental receiver.The output signals of BF network 12 are the sum Σ and difference Δsignals which are processed in a processor 14 to generate an outputsignal θ representing the direction of arrival estimation. Beamformingnetwork 12 is more fully illustrated in FIG. 2. The beamforming networkcomprises signal splitters 21, weighting networks (for multiplicationfunction) 22 and adders 23. Each of the N input signals is split intotwo paths, linearly weighted, and the signals in each of the two pathsare then added together.

The sum Σ and difference Δ signals are given by equations (1) and (2) as

    Σ=W.sub.Σ.sup.H x                              (1)

    Δ=W.sub.Δ.sup.H x                              (2)

respectively. When there is no jamming, Taylor and Bayliss weightingsare typically used for sum beams and difference beams, respectively, soas to have a narrow mainlobe and low sidelobes. In the presence ofjamming, the weights are adapted so as to form nulls responsive to thejammers. The quiescent Taylor and Bayliss weightings are designed forreducing the sidelobes in a practical system.

FIG. 3 represents a typical sum beam antenna pattern. The mainlobe ofthe pattern is a central beam 31 surrounded by minor lobes 32, orsidelobes. Typically, it is desired to have a narrow mainlobe, high gainand low sidelobes so that the desired target within the mainlobe isenhanced and the response to clutter and jamming outside the mainlobe isattenuated.

Typically, one beam (instead of two beams) is formed in transmission,and two beams are formed on reception for angle measurement. As shown inFIG. 4, the sum beam output signal 41 has a symmetrical amplitudeprofile with its maximum at the boresight, and the difference beamoutput signal 42 has an antisymmetrical amplitude profile with zeroresponse at the boresight. The DOA of a target signal can be determinedaccurately through a look-up table by evaluating the monopulse ratio 51,i.e., the real part of Δ/Σ as shown in FIG. 5. For a noiseless case andfor uniform weighting, the monopulse ratio is exactly given by equation(3) as ##EQU4##

Thus, T and the corresponding θ can be determined exactly. For zero-meannoise, the estimator is unbiased with mean square error (MSE) given byequation (4) as ##EQU5## the monopulse sensitivity factor, which isdefined earlier.

This technique can also be considered for use with a planar array wherethe target azimuth and evaluation angles are desired, as shown in FIG.6. In this setup, a column beamformer 65 for each column of sensors 66forms a set 61 of sum beams Σ_(e1) through Σ_(eN) and a set 62 ofdifference beams Δ_(e1) through Δ_(eN) along the elevation axis withinput signals from each column of sensors 66. The Σ_(e) beams are thenlinearly combined in a row beamformer 63 to form signals representingthe sum (Σ=Σ_(a) Σ_(e)) and difference (Δ_(A) =Δ_(a) Σ_(e)) beams alongthe azimuth axis. Similarly, the Δ_(e) beams are linearly combined in arow beamformer 64 to form signals representing the sum (Δ_(E) =Σ_(a)Δ_(e)) and difference (Δ.sub.Δ =Δ_(a) Δ_(e)) beams along the azimuthaxis. Monopulse ratios along azimuth or elevation direction can then beformed giving the azimuth and elevation DOA estimates by using equations(5) and (6)as set forth supra, which take advantage of the separableproperty of the planar array patterns.

The present invention provides cancellation of one mainlobe jammer andmultiple sidelobe jammers in a way that enables both target detectionand unbiased monopulse angle measurement. In order to show themotivation for the present invention, a review is first presented ofsome existing approaches for jammer cancellation. These include thesum-difference mainlobe canceller (MLC) described by S. P. Applebaum andR. Wasiewicz in Main Beam Jammer Cancellation for Monopulse Sensors,Final Tech. Report DTIC RADC-TR-86-267, December, 1984, and the adaptivearray (AA) described by S. P. Applebaum in Adaptive Arrays, SyracuseUniv. Research Corp. , Rep SPL-769, June 1964, and Widrow et al. inAdaptive Antenna Systems, Proc. IEEE, Vol. 55, December 1967.

Sum-Difference Mainlobe Canceller

The sum-difference mainlobe canceller (MLC) is shown in FIG. 7. In theexample illustrated, a single parabolic antenna 70 is used to generatethe sum (Σ) and difference (Δ) signals. The high mainlobe gain outputsignal of the difference beam can be used to null the mainlobe jammer inthe sum beam signal.

Except at the boresight, the difference beam has a high gain and thuscan be used for cancelling the mainlobe jammer without introducingexcessive noise in the main antenna. Suppose the jammer is at T_(j),where T_(j) is the direction cosine of the jammer. The optimal weightfor cancelling the jammer is given approximately by ##EQU6## The weightW is given as the ratio of cross-correlation of sum and difference beamoutput signals to the auto-correlation of the difference beam outputsignaler and is closely approximated by equation (7) for largejammer-to-noise ratio (JNR). Since Σ and Δ beams have comparable gainwithin the mainbeam, weight W would be a moderate number. If low gainauxiliary elements are used for mainlobe jamming cancellation, largeweights are required for cancelling the jammer in the mainbeam, thusintroducing high levels of noise into the system.

S. P. Applebaum et al. in the aforementioned Report DTIC RADC-TR-86-267expanded on this idea and developed an architecture and algorithm fornulling the mainlobe jammer while preserving the monopulse ratio. TheApplebaum et al. technique makes use of the idea that the patterns ofthe received beam are separable in azimuth and elevation, that is, thepatterns can be expressed as products of sum and difference factors inboth azimuth and elevation, i.e., Σ=Σ_(a) Σ_(e), Δ_(A) =Δ_(a) Δ_(e),Δ_(E) =Σ_(a) Δ_(e), Δ.sub.Δ=Δ_(a) Δ_(e)).

The mainlobe canceller (MLC) architecture is shown in FIG. 8. In orderto form the monopulse ratio along the elevation, the Σ and Δ_(E) beamscan be adapted by the Δ_(A) and Δ.sub.Δ beams to form Σ' and Δ_(E) beamsas follows:

    Σ'=Σ-W.sub.a1 Δ.sub.A                    (8)

    Δ.sub.E =Δ.sub.E -W.sub.a2 Δ.sub.Δ (9)

where W_(a1) and W_(a2) are adaptation weights determined as set forth,infra. The adaptation of Equation (8) is implemented with a multiplier81 and summer 80. Multiplier 81 receives as input signals adaptationweight W_(a1) and the Δ_(A) beam output signal, and the product issummed in summer 80 with the Σ beam output signal. Similarly, theadaptation of Equation (9) is implemented with a multiplier 83 andsummer 82. Multiplier 83 receives as input signals adaptation weightW_(a2) and the Δ.sub.Δ beam output signal, and the product is summed insummer 82 with the Δ_(E) beam output signal. The output signals ofsummers 80 and 82, i.e., Σ' and Δ'_(E), are supplied to a processor 84which generates the elevation monopulse ratio Δ'_(E) /Σ'.

One mainlobe jammer can be cancelled along the azimuth by choosing thefollowing adaptation weights Wa1 and Wa2 to minimize output signals forEquations (8) and (9): ##EQU7## The cross-correlation R.sub.ΣΔ.sbsb.Abetween Σ and Δ_(A) channels may be expressed as

    Σ.sub.ΣΔ.sbsb.A =E[ΣΔ.sub.A.sup.* ],

where E, the expectation, can be obtained by ensemble cross-correlationgiven by ##EQU8##

Similarly,

    R.sub.Δ.sbsb.A.sub.Δ.sbsb.A =E[Δ.sub.A Δ.sub.A *],(12)

    R.sub.Δ.sbsb.E.sub.Δ.sbsb.Δ =E[Δ.sub.E Δ.sub.Δ *],

    and

    R.sub.Δ.sbsb.Δ.sub.Δ.sbsb.Δ =E[Δ.sub.Δ Δ.sub.Δ *]

where the symbol * signifies complex conjugate. W_(a1) should be equalto W_(a2) analytically. In practice, however, W_(a1) may not be equal toW_(a2), as the weights are determined by data samples. In that case, wemay force them to be equal (e.g., adapt W_(a) in the Σ channel and useit in the Δ channel or vice versa, or set ##EQU9## i.e., choose theweight to be the average of the adapted weights). The monopulse ratiofor the elevation angle estimation f_(e) (θ_(e)), where f_(e) is theratio of the adapted difference-elevation beam output signal to theadapted sum beam output signal, is obtained in processor 84 in thefollowing manner: ##EQU10## Thus, the monopulse ratio along theelevation direction is maintained (except at the azimuth angle wherethere is a jammer), and the mainlobe jammer is cancelled.

Cancellation of the mainlobe jammer and maintaining the monopulse ratioalong the azimuth direction can be developed in a similar manner. Theadapted sum and difference beams Σ" and Δ_(A), respectively, are givenby

    Σ"=-W.sub.e1 Δ.sub.E, and                      (14)

    Δ'.sub.A =Δ.sub.A -W.sub.e 2 Δ.sub.Δ,(15)

where W_(e1) and W_(e2) are adaptation weights determined as set forth,infra. The adaptation of Equation (14) is implemented with a multiplier86 and summer 85. Multiplier 86 receives as input signals adaptationweight W_(e1) and the Δ_(E) beam, and the product is summed in summer 85with the Σ beam. Similarly, the adaptation of Equation (15) isimplemented with a multiplier 88 and summer 87. Multiplier 88 receivesas input signals adaptation weight W_(e2) and the Δ.sub.Δ beam, and theproduct is summed in summer 87 with the Δ_(A) beam. The output signalsof summers 85 and 87, i.e., Σ" and Δ_(A), are supplied to a processor 89which generates the azimuth monopulse ratio Δ'_(A) /Σ".

The mainlobe jammer can be cancelled by choosing the following adaptiveweights: ##EQU11## Similarly, the weights can be set equal ##EQU12##

The monopulse ratio for the azimuth angle θ_(a) estimate can then beshown to be preserved: ##EQU13## Adaptive Array

Adaptive receiving arrays for radar, which maximize the signal-to-noiseratio at the array output, were first developed by S. P. Applebaum inreport SPL-769, supra. These arrays maximize the ratio of antenna gainin a specified scan direction to the total noise in the output signal.Similar techniques have been described for communications systems byWidrow et al., supra, which minimize the mean square error between thearray output signal and a transmitted pilot signal which is known apriori at the receiver. The theory of adaptive arrays as applied to theangle measurement problem has been developed by R. C. Davis, L. E.Brennan and I. S. Reed, "Angle Estimation with Adaptive Arrays inExternal Noise Field" IEEE Trans on Aerospace and Electronic Systems,Vol. AES-12, No. 2, March 1976. The Davis et al. analysis of usingmaximum likelihood theory of angle estimation leads naturally to theadaptive sum and difference beams.

The array architecture is shown in FIG. 9. The sum and difference beams,represented by the symbols Σ and Δ, respectively, at array outputs 91and 92, respectively, are determined by adaptive receiving arraytechniques which serve to null the interference sources. Because of theadaptivity which involves using multipliers 93 to apply an adaptiveweight at multiplier inputs 94 to antenna array signals furnished atmultiplier inputs 90, the two patterns vary with the external noisefield and are distorted relative to the conventional monopulse sum anddifference beams which possess even and odd symmetry, respectively,about a prescribed boresight angle. The adaptive weights for the sum anddifference beams are given by

    W.sub.Σ= R.sup.-1 W.sub.Σ, and                 (19)

    W.sub.Δ= R.sup.-1 W.sub.Δ,                     (20)

where W.sub.Σ and W.sub.Δ are the nominal sum and difference weightsused in a conventional monopulse system and R is the covariance matrixof the total interference, which may include jamming and noise. Theantenna patterns are distorted according to the following expressions,where S represents the target signal response vector: ##EQU14##

The resulting monopulse ratio is distorted and equal to ##EQU15## whereRe signifies the real part of the expression, and the ideal monopulseratio is ##EQU16##

This technique cancels both the mainlobe and sidelobe jammers butdistorts the monopulse ratio. This approach for DOA estimation has beenverified by computer simulation to work well for SLJs, but performancedegrades when the jammers are within the mainbeam.

Techniques for simultaneous nulling in the sum and difference channelsof a monopulsed phased array using one set of adaptive weights shared byboth beams can be found in L. Haupt, "Simultaneous Nulling in the Sumand Difference Patterns of a Monopulse Antenna," IEEE Trans. on Antennasand Propagation, Vol. AP-32, No. 5, May 1984, pp. 486-493; L Haupt,"Adaptive Nulling in Monopulse Antennas," IEEE Trans. on Antennas andPropagation, Vol. 36, No. 2, February 1988, pp. 202-208; and B. Vu,"Simultaneous Nulling in Sum and Difference Patterns by AmplitudeControl," IEEE Trans. on Antennas and Propagation, Vol. 34, No. 2,February 1986. It should be noted that nulls may be inserted in the twopatterns by using separate adaptive weights and controls for the sum anddifference channels. However, this would require two sets of adaptivebeamforming hardware. Moreover, inserting a null in the sum does notautomatically insert a null in the difference pattern and vice versa.Thus, attempts to adapt the beams separately to null the jammers willcancel the jammers but will also distort the monopulse ratio, thusimpairing its usefulness for DOA estimation. Monopulse processing forDOA estimation requires simultaneous adaptation of the sum anddifference beams.

Adaptive DBF Array followed by a Mainlobe Canceller

FIG. 10 shows a specific implementation of the invention. Thisimplementation is a two-stage digital beamforming (DBF) architecture foradaptive monopulse processing.

There are N columns in the DBF array, and each column has a columnbeamformer 65 for combining the M elemental sensors 66 input signals. Ateach column, the two beams (Σ_(en) and Δ_(en)) are formed by linearlycombining input signals from each set of sensors. They are thendigitized and beamformed, giving

    Σ=W.sub.ΣΣ.sup.H Σ.sub.e ,         (25)

    Δ.sub.A =W.sub.ΔΣ.sup.H Σ.sub.e ,  (26)

    Δ.sub.E =W.sub.ΣΔ.sup.H Δ.sub.e , and (27)

    Δ.sub.Δ =W.sub.ΔΔ.sup.H Δ.sub.e ,(28)

where

    W.sub.ΣΣ =R.sub.Σ.sbsb.e.sup.-1.sub.Σ.sbsb.e W.sub.Σ,                                            (29)

    W.sub.ΔΣ =R.sub.Σ.sbsb.e.sup.-1.sub.Σ.sbsb.e W.sub.Δ,                                            (30)

    W.sub.ΣΔ =R.sub.Δ.sbsb.e.sup.-1.sub.Δ.sbsb.e W.sub.Σ, and                                        (31)

    W.sub.ΔΔ =R.sub.Δ.sbsb.e.sup.-1.sub.Δ.sbsb.e W.sub.Δ,                                            (32)

and where W.sub.Σ and W.sub.Δ are the nominal sum and differenceweights. Taylor and Bayliss weights are typically used. The samplematrix inverse modifies the weights and corresponds to a nullingpreprocessing responsive to jammers.

A sample matrix inverse approach for jamming cancellation willeffectively form nulls responsive to jammers. If one of the jammers iswithin the mainbeam, a null will be found responsive to the mainlobejammer and the mainbeam will be distorted. In order to maintain themainbeam without distortion, the mainlobe jammer effect must be excludedfrom the covariance matrix estimate. This may be accomplished by usingthe following modified covariance matrix in forming the adopted rowbeamforming weights, i.e. equation (29) through equation (32):

    R=R-P.sub.1 J.sub.1 J.sub.1.sup.H,                         (33)

where R is the original sample matrix, P₁ is the power of the mainlobejammer, and J₁ is the array response vector of the mainlobe jammer. Thismodified covariance matrix does not have the information of the mainlobejammer, and thus there will not be a null responsive to the mainlobejammer. The power and location can be obtained by analyzing thecovariance matrix, such as by using the MUSIC algorithm (see R. Schmidt,"Multiple Emitter Location and Signal Parameter Estimation," IEEE Trans.on Antennas and Propagation, Vol. AP-34, March 1986).

An alternative method for suppressing the mainlobe jammer effect can beperformed by using prefiltering to block the mainlobe jammer. A blockingmatrix B can be designed when the direction of the mainlobe jammer isknown, i.e., by making B orthogonal to the steering vector of themainlobe jammer. The resulting sample vectors will thus be free of themainlobe jammer and can then be used for covariance matrix estimates forsidelobe jammer cancellation.

The technique of preprocessing, together with an example of mainbeamconstraint, is illustrated below. The covariance matrix can bedecomposed into noise covariance and jamming covariance matrices asfollows: ##EQU17## where σ_(n) ² is the elemental noise variance,(JNR)_(k) is the kth jamming-to-noise ratio, and J_(k) is the kthjamming factor. For conventional preprocessing without mainbeammaintenance, R⁻¹ is applied to the vector input before forming the Σ andΔ beams, i.e., ##EQU18## This explicit expression for R⁻¹ is derived forthe case of well-resolved jammers. An example of the technique tomaintain the mainlobe is to apply R' instead of R in the preprocessingstate where R'=R-P₁ J₁ J₁ ^(H), P₁ is the power estimate of the MLJ, J₁is the direction vector estimate within the mainlobe corresponding tothe MLJ, W.sub.Σ is the conventional Σ beam weight, and W.sub.Σ^(H) S isthe ideal sum beam.

An expression for the modified Δ beam can also be derived J_(k) ^(H) Shas an interpretation that the beam is steered to the jammer direction.In order to maintain the Σ beam within the mainlobe, the effect of thejammer within the mainbeam (e.g., the first jammer J₁) is suppressed,i.e., ##EQU19##

It should be noted that summation is from k=2 to k=K. The Δ beam canalso be maintained accordingly; that is, ##EQU20## The product beams,i.e., two-dimensional azimuth and elevation beams) are then free of SLJsbut may include the MLJ. The mainbeam jammer is cancelled by adaptingthe two-dimensional Σ and Δ beams simultaneously. For example, in orderto form the monopulse ratio in elevation, the Σ and Δ beams are adaptedto cancel the MLJ simultaneously as follows:

    Σ'=Σ-w.sub.a Δ.sub.A, and                (37)

    Δ'.sub.E =Δ.sub.E -w.sub.a, Δ.sub.Δ.(38)

This can be done by adapting w_(a) in the Σ channel and using it in theΔ channel, or choosing w_(a) to adapt to the Σ and Δ beamssimultaneously. In this way, the monopulse ratio can be shown to bepreserved along the elevation axis while the jammer is nulled along theazimuth axis as follows: ##EQU21##

The same technique can also be used to preserve the monopulse ratioalong the azimuth with the mainlobe jammer cancelled along theelevation.

While only certain preferred features of the invention have beenillustrated and described herein, many modifications and changes willoccur to those skilled in the art. It is, therefore, to be understoodthat the appended claims are intended to cover all such modificationsand changes as fall within the true spirit of the invention.

What is claimed is:
 1. In a monopulse radar system having an adaptive array antenna, a mainlobe canceller, and a monopulse processor for determining angle of arrival, said adaptive array antenna comprising multiple elemental sensors, said monopulse processor being operable to form target angle of arrival estimation using received sum and difference beam output signals, and said mainlobe canceller being operable to generate said signals representing said sum and difference beams expressed as a product of elevation and azimuth factors for use by said monopulse processor while simultaneously yielding an undistorted elevation angular measurement by cancelling a mainlobe jammer with nulls in azimuth and an undistorted azimuth angular measurement by cancelling said mainlobe jammer with nulls in elevation, the improvement comprising:preprocessing means coupled to said adaptive array antenna for forming an identical set of nulls responsive to jammers before said sum and difference beams are formed for monopulse processing; means for maintaining the mainlobe during preprocessing; and means coupling said adaptive array in cascade with said mainlobe canceller.
 2. The improvement of claim 1, wherein said means for maintaining the mainlobe during preprocessing comprises means for suppressing the effect of the jammer within the mainlobe by removing said jammer during said preprocessing.
 3. A monopulse radar system for nulling a mainlobe jammer and multiple sidelobe jammers, comprising:a plurality of elemental sensors arranged in columns and responsive to received radar signals; column beamformers for combining said plurality of elemental sensors input signals in each of said columns; mainlobe maintenance means coupled to said column beamformers for suppressing the mainlobe jammer; covariance matrix estimation and inversion means coupled to said mainlobe maintenance means; and monopulse processor means for angle estimation using said covariance matrix inversion means and said mainlobe maintenance means for producing a sum signal Σ and a difference signal Δ such that said Σ and Δ signals have an identical set of nulls responsive to said jammers.
 4. The monopulse radar system of claim 3 including weighting means coupling said column beamformers and said mainlobe maintenance means to said monopulse processor means for providing adaptive weighting to output signals from the analog-to-digital conversion means for each of said columns of sensors. 